5 citations · 12 across the 5 of their papers we have counts for
5 papers
Can neural networks understand monotonicity reasoning?
Hitomi Yanaka, Koji Mineshima, Daisuke Bekki +4
Monotonicity reasoning is one of the important reasoning skills for any intelligent natural language inference (NLI) model in that it requires the ability to capture the interactio…
Multimodal Logical Inference System for Visual-Textual Entailment
Riko Suzuki, Hitomi Yanaka, Masashi Yoshikawa +2
A large amount of research about multimodal inference across text and vision has been recently developed to obtain visually grounded word and sentence representations. In this pape…
Automatic Generation of High Quality CCGbanks for Parser Domain Adaptation
Masashi Yoshikawa, Hiroshi Noji, Koji Mineshima +1
We propose a new domain adaptation method for Combinatory Categorial Grammar (CCG) parsing, based on the idea of automatic generation of CCG corpora exploiting cheaper resources of…
HELP: A Dataset for Identifying Shortcomings of Neural Models in Monotonicity Reasoning
Hitomi Yanaka, Koji Mineshima, Daisuke Bekki +4
Large crowdsourced datasets are widely used for training and evaluating neural models on natural language inference (NLI). Despite these efforts, neural models have a hard time cap…
Determining Semantic Textual Similarity using Natural Deduction Proofs
Hitomi Yanaka, Koji Mineshima, Pascual Martinez-Gomez +1
Determining semantic textual similarity is a core research subject in natural language processing. Since vector-based models for sentence representation often use shallow informati…